
Data Mining in Healthcare Quiz
Quiz
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Other
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University
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Hard
Annemieke Corbitt
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8 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the most basic definition of data mining?
Predicting what will happen
Analyzing large data sets to discover patterns
Describing what has happened
Determining what to do about it
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which category of analytics does data mining fall under?
None of the above
Descriptive analytics
Predictive analytics
Prescriptive analytics
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What are the three systems required for effective data mining in healthcare?
Analytics system, best practice system, adoption system
Descriptive analytics, predictive analytics, prescriptive analytics
Data mining system, research system, implementation system
Academic system, clinical system, technology system
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the main advantage of training a predictive algorithm specific to a defined population?
Higher accuracy of the algorithm
Greater flexibility of the algorithm
Faster implementation of the algorithm
Lower cost of implementing the algorithm
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which industry successfully uses data mining to model customer response?
Manufacturing industry
Automotive industry
Telecom industry
Retail industry
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the key to driving real-world improvement with any analytics initiative in healthcare?
Implementing an analytics system
Implementing a best practice system
Implementing an adoption system
Implementing all three systems
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the purpose of the best practice system in healthcare?
To gather data and make sense of it
To apply evidence-based best practices to care delivery
To drive change management through new organizational structures
To build predictive models from vast data stores
8.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the main challenge faced by health systems in implementing data mining initiatives?
Lack of technology adoption
Resistance from clinicians
Lack of available data
Lack of research publications
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